Prediction of key milk biomarkers in dairy cows through milk mid-infrared spectra and international collaborations.

At the individual cow level, suboptimum fertility, mastitis, negative energy balance, and ketosis are major issues in dairy farming. These problems are widespread on dairy farms and have an important economic impact. The objectives of this study were (1) to assess the potential of milk mid-infrared (MIR) spectra to predict key biomarkers of energy deficit (citrate, isocitrate, glucose-6 phosphate [glucose-6P], free glucose), ketosis (ß-hydroxybutyrate [BHB] and acetone), mastitis (N-acetyl-ß-d-glucosaminidase activity [NAGase] and lactate dehydrogenase), and fertility (progesterone); (2) to test alternative methodologies to partial least squares (PLS) regression to better account for the specific asymmetric distribution of the biomarkers; and (3) to create robust models by merging large datasets from 5 international or national projects. Benefiting from this international collaboration, the dataset comprised a total of 9,143 milk samples from 3,758 cows located in 589 herds across 10 countries and represented 7 breeds. The samples were analyzed by reference chemistry for biomarker contents, whereas the MIR analyses were performed on 30 instruments from different models and brands, with spectra harmonized into a common format. Four quantitative methodologies were evaluated to address the strongly skewed distribution of some biomarkers. Partial least squares regression was used as the reference basis, and compared with a random modification of distribution associated with PLS (random-downsampling-PLS), an optimized modification of distribution associated with PLS (KennardStone-downsampling-PLS), and support vector machine (SVM). When the ability of MIR to predict biomarkers was too low for quantification, different qualitative methodologies were tested to discriminate low versus high values of biomarkers. For each biomarker, 20% of the herds were randomly removed within all countries to be used as the validation dataset. The remaining 80% of herds were used as the calibration dataset. In calibration, the 3 alternative methodologies outperform the PLS performances for the majority of biomarkers. However, in the external herd validation, PLS provided the best results for isocitrate, glucose-6P, free glucose, and lactate dehydrogenase (coefficient of determination in external herd validation [R2v] = 0.48, 0.58, 0.28, and 0.24, respectively). For other molecules, PLS-random-downsampling and PLS-KennardStone-downsampling outperformed PLS in the majority of cases, but the best results were provided by SVM for citrate, BHB, acetone, NAGase, and progesterone (R2v = 0.94, 0.58, 0.76, 0.68, and 0.15, respectively). Hence, PLS and SVM based on the entire dataset provided the best results for normal and skewed distributions, respectively. Complementary to the quantitative methods, the qualitative discriminant models enabled the discrimination of high and low values for BHB, acetone, and NAGase with a global accuracy around 90%, and glucose-6P with an accuracy of 83%. In conclusion, MIR spectra of milk can enable quantitative screening of citrate as a biomarker of energy deficit and discrimination of low and high values of BHB, acetone, and NAGase, as biomarkers of ketosis and mastitis. Finally, progesterone could not be predicted with sufficient accuracy from milk MIR spectra to be further considered. Consequently, MIR spectrometry can bring valuable information regarding the occurrence of energy deficit, ketosis, and mastitis in dairy cows, which in turn have major influences on their fertility and survival.

Influence of the concentrate inclusion level in a grass silage-based diet on hepatic transcriptomic profiles in Holstein-Friesian dairy cows in early lactation.

Excessive negative energy balance in early lactation is linked to an increased disease risk but may be mitigated by appropriate nutrition. The liver plays central roles in both metabolism and immunity. Hepatic transcriptomic profiles were compared between 3 dietary groups in each of 40 multiparous and 18 primiparous Holstein-Friesian cows offered isonitrogenous grass silage-based diets with different proportions of concentrates: (1) low concentrate (LC, 30% concentrate + 70% grass silage); (2) medium concentrate (MC, 50% concentrate + 50% grass silage), or (3) high concentrate (HC, 70% concentrate + 30% grass silage). Liver biopsies were taken from all cows at around 14 d in milk for RNA sequencing, and blood metabolites were measured. The sequencing data were analyzed separately for primiparous and multiparous cows using CLC Genomics Workbench V21 (Qiagen Digital Insights), focusing on comparisons between HC and LC groups. More differentially expressed genes (DEG) were seen between the primiparous cows receiving HC versus LC diets than for multiparous cows (597 vs. 497), with only 73 in common, indicating differential dietary responses. Multiparous cows receiving the HC diet had significantly higher circulating glucose and insulin-like growth factor-1 and lower urea than those receiving the LC diet. In response to HC, only the multiparous cows produced more milk. In these animals, bioinformatic analysis indicated expression changes in genes regulating fatty acid metabolism and biosynthesis (e.g., ACACA, ELOVL6, FADS2), increased cholesterol biosynthesis (e.g., CYP7A1, FDPS, HMGCR), downregulation in hepatic AA synthesis (e.g., GPT, GCLC, PSPH, SHMT2), and decreased expression of acute phase proteins (e.g., HP, LBP, SAA2). The primiparous cows on the HC diet also downregulated genes controlling AA metabolism and synthesis (e.g., CTH, GCLC, GOT1, ODC1, SHMT2) but showed higher expression of genes indicative of inflammation (e.g., CCDC80, IL1B, S100A8) and fibrosis (e.g., LOX, LUM, PLOD2). This potentially adverse response to a HC diet in physically immature animals warrants further investigation.

Effect of diet and nonesterified fatty acid levels on global transcriptomic profiles in circulating peripheral blood mononuclear cells in early lactation dairy cows.

After calving, lipid mobilization caused by increased nutrient demands for lactation leads to elevated circulating concentrations of nonesterified fatty acids (NEFA). Excessive NEFA levels have previously been identified as a major risk factor for postpartum immunosuppression. The aim of this study was to investigate changes in global transcriptomic gene expression of peripheral blood mononuclear cells (PBMC) in dairy cows offered different early lactation diets (high concentrate, n = 7; medium, n = 8; or low, n = 9) and with differing circulating levels of NEFA. Cows were classified as having NEFA concentrations of either <500 µM (low, n = 6), 500 to 750 µM (medium, n = 8) or >750 µM (high, n = 10) at 14 d in milk. Plasma urea concentrations were greater for cows on the high concentrate diet but ß-hydroxybutyrate and glucose concentrations did not differ significantly between either dietary treatments or NEFA groups. Cows with high NEFA weighed more at drying off and suffered greater body condition score loss after calving. The PBMC were isolated at 14 d in milk, and RNA was extracted for RNA sequencing. Differential gene expression was analyzed with DESeq2 with q-value for false discovery rate control followed by Gene Ontology Enrichment. Although there were no differentially expressed genes associated with lactation diet, 304 differentially expressed genes were identified between cows with high and low circulating NEFA, with 118 upregulated and 186 downregulated. Gene Ontology enrichment analysis demonstrated that biological adhesion and immune system process were foremost among various PBMC functions which were altered relating to body defenses and immunity. High NEFA concentrations were associated with inhibited cellular adhesion function by downregulating 20 out of 26 genes (by up to 17-fold) related to this process. Medium NEFA concentrations altered a similar set of functions as high NEFA, but with smaller enrichment scores. Localization and immune system process were most significant, with biological adhesion ranking only eleventh. Our results demonstrated that increased circulating NEFA concentrations, but not diet, were associated with immune system processes in PBMC in early lactation cows. Leukocyte cell-to-cell adhesion was inhibited when the NEFA concentration exceeded 750 µM, which would reduce the efficiency of diapedesis and so contribute to decreased body defense mechanisms and predispose animals to infection.

Potential of milk mid-infrared spectra to predict nitrogen use efficiency of individual dairy cows in early lactation.

Improving nitrogen use efficiency (NUE) at both the individual cow and the herd level has become a key target in dairy production systems, for both environmental and economic reasons. Cost-effective and large-scale phenotyping methods are required to improve NUE through genetic selection and by feeding and management strategies. The aim of this study was to evaluate the possibility of using mid-infrared (MIR) spectra of milk to predict individual dairy cow NUE during early lactation. Data were collected from 129 Holstein cows, from calving until 50 d in milk, in 3 research herds (Denmark, Ireland, and the UK). In 2 of the herds, diets were designed to challenge cows metabolically, whereas a diet reflecting local management practices was offered in the third herd. Nitrogen intake (kg/d) and nitrogen excreted in milk (kg/d) were calculated daily. Nitrogen use efficiency was calculated as the ratio between nitrogen in milk and nitrogen intake, and expressed as a percentage. Individual daily values for NUE ranged from 9.7 to 81.7%, with an average of 36.9% and standard deviation of 10.4%. Milk MIR spectra were recorded twice weekly and were standardized into a common format to avoid bias between apparatus or sampling periods. Regression models predicting NUE using milk MIR spectra were developed on 1,034 observations using partial least squares or support vector machines regression methods. The models were then evaluated through (1) a cross-validation using 10 subsets, (2) a cow validation excluding 25% of the cows to be used as a validation set, and (3) a diet validation excluding each of the diets one by one to be used as validation sets. The best statistical performances were obtained when using the support vector machines method. Inclusion of milk yield and lactation number as predictors, in combination with the spectra, also improved the calibration. In cross-validation, the best model predicted NUE with a coefficient of determination of cross-validation of 0.74 and a relative error of 14%, which is suitable to discriminate between low- and high-NUE cows. When performing the cow validation, the relative error remained at 14%, and during the diet validation the relative error ranged from 12 to 34%. In the diet validation, the models showed a lack of robustness, demonstrating difficulties in predicting NUE for diets and for samples that were not represented in the calibration data set. Hence, a need exists to integrate more data in the models to cover a maximum of variability regarding breeds, diets, lactation stages, management practices, seasons, MIR instruments, and geographic regions. Although the model needs to be validated and improved for use in routine conditions, these preliminary results showed that it was possible to obtain information on NUE through milk MIR spectra. This could potentially allow large-scale predictions to aid both further genetic and genomic studies, and the development of farm management tools.

Deriving estimates of individual variability in genetic potentials of performance traits for 3 dairy breeds, using a model of lifetime nutrient partitioning.

This study explored the ability of an existing lifetime nutrient partitioning model for simulating individual variability in genetic potentials of dairy cows. Generally, the model assumes a universal trajectory of dynamic partitioning of priority between life functions and genetic scaling parameters are then incorporated to simulate individual difference in performance. Data of 102 cows including 180 lactations of 3 breeds: Danish Red, Danish Holstein, and Jersey, which were completely independent from those used previously for model development, were used. Individual cow performance records through sequential lactations were used to derive genetic scaling parameters for each animal by calibrating the model to achieve best fit, cow by cow. The model was able to fit individual curves of body weight, and milk fat, milk protein, and milk lactose concentrations with a high degree of accuracy. Daily milk yield and dry matter intake were satisfactorily predicted in early and mid lactation, but underpredictions were found in late lactation. Breeds and parities did not significantly affect the prediction accuracy. The means of genetic scaling parameters between Danish Red and Danish Holstein were similar but significantly different from those of Jersey. The extent of correlations between the genetic scaling parameters was consistent with that reported in the literature. In conclusion, this model is of value as a tool to derive estimates of genetic potentials of milk yield, milk composition, body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise. The model enables simulation of the effects of a genetic selection strategy on lifetime efficiency of individual cows, which has a main advantage of including the rearing costs, and thus, can be used to explore the impact of future selection on animal performance and efficiency.

Short communication: Changes in gait symmetry in healthy and lame dairy cows based on 3-dimensional ground reaction force curves following claw trimming.

Lameness is a frequent health problem in dairy cows. This preliminary study aimed to detect gait differences between healthy and lame walking cows using 3-dimensional force plates. We examined left-right leg symmetry changes of healthy and lame Holstein dairy cows following claw trimming. Gait scoring (GS) was performed on d -5, 0, 1, and 7 relative to claw trimming. Before the experiment, 5 cows walked normally (initial GS=1) and 4 cows limped moderately on a hind leg (initial GS=3). Gait was measured on d -2, -1, 0, 1, and 7 relative to trimming by obtaining ground reaction forces as cows walked repeatedly across 2 parallel 3-dimensional force plates. From the ground reaction forces, stance phase data were derived using computerized procedures. Left-right leg symmetries of entire curves in the 3 force directions were calculated. Effects of lameness and trimming were analyzed in a mixed model, using a low lameness threshold (GS>1). One week after claw trimming, only one cow was mildly lame. In addition, the symmetries of all 3 dimensions were significantly improved shortly after trimming. Importantly, lameness significantly worsened vertical symmetry. Lame cows walked significantly more slowly than healthy cows. In conclusion, all force symmetries seemed capable of detecting gait responses to claw trimming. Although our results are based on a small number of animals, vertical leg symmetry was affected by lameness.

Generation of an index for physiological imbalance and its use as a predictor of primary disease in dairy cows during early lactation.

Physiological imbalance (PI) is a situation in which physiological parameters deviate from the normal and cows consequently have an increased risk of developing production diseases and reduced production or reproduction. The objectives of this work were (1) to generate an index for PI based on several plasma metabolites and (2) to compare the use of this index with calculated energy balance (EBAL) and individual plasma metabolites in relation to risk of disease during early lactation. We used a total of 634 lactations from 317 cows consisting of 3 breeds ranging from a parity of 1 to 4. Weekly blood samples were analyzed for selected metabolites; that is, urea nitrogen, albumin, cholesterol, nonesterified fatty acids (NEFA), glucose, and ß-hydroxybutyrate (BHBA). Energy intake and EBAL were calculated; veterinary treatment records and daily composite milk somatic cell counts were used to determine incidence of disease. Data were adjusted for numerous fixed effects (e.g., parity, breed, and week around calving) before further statistical analysis. The time of disease (TOD) was recorded as the day in which the signs of disease were observed (TOD=0). The week before and after TOD was ± n wk relative to TOD=0. Each week, all plasma metabolites were individually adjusted to an overall mean (=0) and variance (=1). The normalized variables were included in regression analyses by week of lactation to identify metabolites that explain the variation in calculated EBAL, as a reflection of degree of PI. Nonesterified fatty acids, BHBA, and glucose were weighted within each week based on regression coefficients (i.e., x1-x3 below) generated from a model to predict EBAL. Data from wk -1 relative to TOD were analyzed using a mixed linear model to relate degree of PI and metabolites in blood to risk of disease. The weekly PI index was defined as PI=(x1 × [NEFA])+x2 × [BHBA] - x3 × [glucose])/3. For diseases that developed ≥ 2 wk after calving, no variables were associated with risk of disease. Prepartal PI and plasma NEFA were better predictors of disease (i.e., metritis, retained placenta, and milk fever) at wk 1 than EBAL and plasma BHBA and glucose. Examining the relationship between PI and milk constituents is needed for the development of an automated in-line and real-time surveillance system for early detection of risk animals on-farm.

Gram-typing of mastitis bacteria in milk samples using flow cytometry.

Fast identification of pathogenic bacteria in milk samples from cows with clinical mastitis is central to proper treatment. In Denmark, time to bacterial diagnosis is typically 24 to 48 h when using traditional culturing methods. The PCR technique provides a faster and highly sensitive identification of bacterial pathogens, although shipment of samples to diagnostic laboratories delays treatment decisions. Due to the lack of fast on-site tests that can identify the causative pathogens, antibiotic treatments are often initiated before bacterial identification. The present study describes a flow cytometry-based method, which can detect and distinguish gram-negative and gram-positive bacteria in mastitis milk samples. The differentiation was based on bacterial fluorescence intensities upon labeling with biotin-conjugated wheat germ agglutinin and acridine orange. Initially 19 in-house bacterial cultures (4 gram-negative and 15 gram-positive strains) were analyzed, and biotin-conjugated wheat germ agglutinin and acridine orange florescence intensities were determined for gram-negative and gram-positive bacteria, respectively. Fluorescence cut-off values were established based on receiver operating characteristic curves for the 19 bacterial cultures. The method was then tested on 53 selected mastitis cases obtained from the department biobank (milk samples from 6 gram-negative and 47 gram-positive mastitis cases). Gram-negative bacteria in milk samples were detected with a sensitivity of 1 and a specificity of 0.74, when classification was based on the previously established cut-off values. However, when receiver operating characteristic curves were constructed for the 53 mastitis cases, results indicate that a sensitivity and specificity of 1 could be reached if cut-off values were reduced. This flow cytometry-based technique could potentially provide dairy farmers and attending veterinarians with on-site information on bacterial gram-type and prevent ineffective antimicrobial treatment in mastitis cases caused by gram-negative bacteria.

Identification of hepatic biomarkers for physiological imbalance of dairy cows in early and mid lactation using proteomic technology.

Identification of biomarkers for degree of physiological imbalance (PI), a situation in which physiological parameters deviate from normal, is needed to reduce disease risk and improve production and reproduction performance of cows. The objective was to describe the liver proteome in early and mid lactation for cows with different degrees of PI with a special focus on biomarkers and pathways involved in periparturient disease complexes. Twenty-nine cows in early [49 ± 22d in milk (DIM); n=14] and mid (159 ± 39 DIM; n=15) lactation were nutrient restricted for 4d to increase PI by supplementing the ration with 60% wheat straw. Liver biopsies were collected -1 and 3d relative to restriction. Before restriction, an index for PI was calculated based on plasma nonesterified fatty acids, ß-hydroxybutyrate, and glucose concentrations. Within E and M cows, a subsets of 6 cow was classified as having either the greatest (PI) or least (normal; N) degree of PI and were used for isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative profiling in liver using liquid chromatography-tandem mass spectrometry. We identified pyruvate carboxylase and isocitrate dehydrogenase as potential hepatic biomarkers for PI for cows during early lactation and alcohol dehydrogenase-4 and methylmalonate-semialdehyde dehydrogenase for cows in mid lactation. This preliminary study identified new biomarkers in liver for PI and provided a better understanding of the differences in coping strategies used for cows in PI. Despite the small sample size (n=3/group), the results lay a foundation for future research focused on the usefulness of the hepatic biomarkers for predicting PI and thereby cows at risk for disease during lactation.

Effects of Bos taurus autosome 9-located quantitative trait loci haplotypes on the disease phenotypes of dairy cows with experimentally induced Escherichia coli mastitis.

Several quantitative trait loci (QTL) affecting mastitis incidence and mastitis-related traits such as somatic cell score exist in dairy cows. Previously, QTL haplotypes associated with susceptibility to Escherichia coli mastitis in Nordic Holstein-Friesian (HF) cows were identified on Bos taurus autosome 9. In the present study, we induced experimental E. coli mastitis in Danish HF cows to investigate the effect of 2 E. coli mastitis-associated QTL haplotypes on the cows' disease phenotypes and recovery in early lactation. Thirty-two cows were divided in 2 groups bearing haplotypes with either low (HL) or high (HH) susceptibility to E. coli. In addition, biopsies (liver and udder) were collected from half of the cows (n=16), resulting in a 2 × 2 factorial design, with haplotype being one factor (HL vs. HH) and biopsy being the other factor (biopsies vs. no biopsies). Each cow was inoculated with a low E. coli dose (20 to 40 cfu) in one front quarter at time 0 h. Liver biopsies were collected at -144, 12, 24, and 192 h; udder biopsies were collected at 24h and 192 h post-E. coli inoculation. The clinical parameters: feed intake, milk yield, body temperature, heart rate, respiration rate, rumen motility; and the paraclinical parameters: bacterial counts, somatic cell count (SCC), and milk amyloid A levels in milk; and white blood cell count, polymorphonuclear neutrophilic leukocyte (PMNL) count, and serum amyloid A levels in blood were recorded at different time points post-E. coli inoculation. Escherichia coli inoculation changed the clinical and paraclinical parameters in all cows except one that was not infected. Clinically, the HH group tended to have higher body temperature and heart rate than the HL group did. Paraclinically, the HL group had faster PMNL recruitment and SCC recovery than the HH group did. However, we also found interactions between the effects of haplotype and biopsy for body temperature, heart rate, and PMNL. In conclusion, when challenged with E. coli mastitis, HF cows with the specific Bos taurus autosome 9-located QTL haplotypes were associated with differences in leukocyte kinetics, with low-susceptibility cows having faster blood PMNL recruitment and SCC recovery and a tendency for a milder clinical response than the high-susceptibility cows did.

Test accuracy of metabolic indicators in predicting decreased fertility in dairy cows.

Negative energy balance is a known risk factor for decreased fertility in dairy cows. This study evaluated the accuracy of plasma concentrations of nonesterified fatty acids (NEFA), ß-hydroxybutyrate (BHBA), and insulin-like growth factor 1 (IGF-1)-factors related to negative energy balance-in predicting decreased fertility. One plasma sample per cow was collected from 480 cows in 12 herds during the period from d 4 to 21 in milk and analyzed for NEFA, BHBA, and IGF-1. For each cow, data on breed, parity, calving date, gynecological examinations, and insemination dates were obtained. Milk samples from 241 cows in 7 of the participating herds were analyzed for progesterone concentration to define the first day of luteal activity. The diagnostic sensitivity (Se) and specificity (Sp) at different cut-off concentrations of NEFA, BHBA, or IGF-1 were calculated and related to individual cow fertility status, measured as anestrus (ANEST), delayed first artificial insemination (DFAI), or delayed conception. Positive and negative predictive values (PV+; PV-) were calculated considering different levels of (within-herd) prevalence. Strata (i.e., subgroup)-specific Se and Sp and associations between test results and fertility parameters were investigated using logistic regression. The NEFA and BHBA tests for ANEST and DFAI had the highest combined Se and Sp and were thus evaluated further. Cut-off values with Sp around 80% were used in this step to provide a reasonable number of test-positive cows, representing a practical situation. This corresponded to a cut-off value for the NEFA test of 400 µEq/L (Se 0.27-0.45) and for the BHBA test of 1.8mM (Se 0.15-0.30) across all cows included in the study. The estimated Sp was generally higher than the original 80%, but the corresponding Se was further decreased when the test was used in heifers compared with older cows. The true prevalence of ANEST in the study population was 27%, which gave a PV+ of 0.36 to 0.45 and a PV- of 0.76 to 0.79. With 35% true prevalence of DFAI, PV+ was 0.29 to 0.38 and PV- was 0.64 to 0.66. Thus, overall test performance was low when metabolic indicators measured as single values in early lactation were used to predict fertility in dairy cows, but accuracy was influenced by cow-level factors such as parity. The prevalence of the target condition (in this case, decreased fertility) also influences test usefulness and should be considered when planning test systems and interpreting test results.

Supplemental feeding with glycerol or propylene glycol of dairy cows in early lactation--effects on metabolic status, body condition, and milk yield.

The objective of this field study was to evaluate the effect of supplemental feeding with glycerol or propylene glycol to dairy cows in early lactation on metabolic status, body condition and milk yield. In total, 673 newly calved cows from 12 commercial Swedish dairy herds were randomized to daily supplementation with 450 g of glycerol (GLY), 300 g of propylene glycol (PG), or nothing (control, CON). Supplements were fed twice daily from 0 to 21 d in milk (DIM) as a top dress on concentrates. For each cow, data on parity, breed, calving date, monthly test-day milk yield, and cases of diseases were collected. Blood samples were taken at approximately 2, 5, and 8 wk postpartum (pp) and analyzed for glucose, ß-hydroxybutyrate (BHBA), nonesterified fatty acids (NEFA), and insulin. Samples taken within 3 wk pp were also analyzed for insulin-like growth factor 1 (IGF-1). Measurements of body condition score (BCS) and heart girth (HG) were obtained at approximately 2 and 5 wk pp and at time of first insemination. The effects of supplemental feeding with GLY or PG on the plasma concentrations of glucose, NEFA, BHBA, insulin, and IGF-1, and BCS, HG, and occurrence of disease were analyzed. No differences in BCS or HG or in plasma concentrations of glucose, BHBA, NEFA, or IGF-1 were found between the control group and any of the treatment groups. Cows in the GLY group had lower plasma insulin concentrations during DIM 0 to 63 compared with group CON, but no difference in insulin was found between the PG group and the CON group. Cows supplemented with GLY had a higher milk yield (kg of milk and kg of energy-corrected milk) during the first 90 DIM. Cows in the PG group tended to yield more milk during the same period. No differences in the occurrence of diseases were seen between the groups. In conclusion, supplementation with GLY in early lactation did increase milk yield without a subsequent decrease of metabolic status, and supplementation with PG tended to do the same.

Liver protein expression in dairy cows with high liver triglycerides in early lactation.

Fatty liver is a frequent subclinical health disorder in dairy cows that may lead to disorders related to the liver function. However, the effect of triglyceride (TG) accumulation on liver metabolic pathways is still unclear. The objective was, therefore, to characterize quantitative differences in the liver proteome between early lactation dairy cows with a low or high liver TG content. The liver proteome analysis indicated that a high liver TG content in early lactation dairy cows is associated with increased oxidation of saturated fatty acids, oxidative stress, and urea synthesis and decreased oxidation of unsaturated fatty acids. Furthermore, liver gluconeogenesis is apparently not impaired by an increased liver TG content. Based on correlations between liver proteins and plasma components, we suggest that future studies investigate the sensitivity and specificity of plasma aspartate aminotransferase, ß-hydroxybutyrate, total bilirubin, total bile acids, and γ-glutamyltransferase for potential use as blood-based biomarkers for early detection of fatty liver in dairy cows. Our study is the first to study the proteome of dairy cows with naturally occurring fatty liver in early lactation.

Metabolic and production profiles of dairy cows in response to decreased nutrient density to increase physiological imbalance at different stages of lactation.

Physiological imbalance (PI) is a situation in which physiological parameters deviate from the normal, and cows consequently have an increased risk of developing production diseases and reduced production or reproduction. Our objectives were to (1) determine the effect of stage of lactation and milk yield on metabolic and production responses of cows during a nutrient restriction period to experimentally increase PI; (2) identify major metabolites that relate to degree of PI; and (3) identify potential biomarkers in milk for on-farm detection of PI throughout lactation. Forty-seven Holstein cows in early [n=14; 49±22 d in milk (DIM); parity=1.6±0.5], mid (n=15; 159±39 DIM; parity=1.5±0.5), and late (n=18; 273±3 DIM; parity=1.3±0.5) lactation were used. Prior to restriction, all cows were fed the same total mixed ration ad libitum. All cows were then nutrient restricted for 4 d by supplementing the ration with 60% wheat straw to induce PI. After restriction, cows returned to full feed. Daily milk yield was recorded and composite milk samples were analyzed for fat, protein, lactose, citrate, somatic cells, uric acid, alkaline phosphatase, ß-hydroxybutyrate (BHBA), and milk urea nitrogen. Blood was collected daily and analyzed for metabolites: nonesterified fatty acids (NEFA), BHBA, glucose, plasma urea nitrogen, and insulin. The revised quantitative insulin sensitivity check index (RQUICKI) was calculated for each cow. Liver biopsies collected before and during restriction were analyzed for triglycerides, glycogen, phospholipids, glucose, and total lipid content. A generalized linear mixed model was used to determine the effect of stage of lactation on responses during restriction. Regression analyses were used to examine the effect of pre-restriction levels on changes during restriction. Similar decreases in milk yield among groups indicate that the capacity of individual responses is dependent on milk yield but the coping strategies used are dependent on stage of lactation. Milk yield was a better predictor of feed intake than DIM. Plasma glucose decreased for all cows, and cows in early lactation had increased plasma BHBA, whereas cows in later lactation had increased NEFA during restriction. Milk citrate had the greatest increase (58%) during restriction for all cows. Results reported here identified metabolites (i.e., glucose, NEFA, BHBA, cholesterol) as predictors of PI and identified milk citrate as a promising biomarker for PI on farm.

Between- and within-herd variation in blood and milk biomarkers in Holstein cows in early lactation.

Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (ß-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-ß-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites' levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring.

Cytokine and acute phase protein gene expression in repeated liver biopsies of dairy cows with a lipopolysaccharide-induced mastitis.

A minimally invasive liver biopsy technique was tested for its applicability to study the hepatic acute phase response (APR) in dairy cows with Escherichia coli lipopolysaccharide (LPS)-induced mastitis. The hepatic mRNA expression profiles of the inflammatory cytokines, tumor necrosis factor alpha (TNF-alpha), IL-1beta, IL-6, and IL-10, and the acute phase proteins serum amyloid A isoform 3 (SAA3), haptoglobin (Hp), and alpha(1)-acid glycoprotein (AGP) were determined by real-time reverse transcription-PCR. Fourteen primiparous cows in mid lactation were challenged with 200 microg of LPS (n = 8) or NaCl solution (n = 6) in 1 front quarter. Six repeated liver biopsies were collected at -22, 3, 6, 9, 12, and 48 h relative to LPS challenge in 4 LPS-infused cows and 3 NaCl-infused cows. The remaining cows had 3 liver biopsies taken at -22, 9, and 48 h. Production data and clinical signs were recorded and white blood cell counts and somatic cell counts (SCC) were analyzed to investigate the effect of repeated liver biopsies and verify the LPS model. Plasma concentrations of TNF-alpha, SAA3, Hp, and AGP were determined for comparison with the liver expression data. Repeated liver biopsies had no effects on the production data, clinical signs, or APR of dairy cows. Compared with the NaCl-infused cows the LPS-infused cows responded to the LPS treatment by increased body temperature (38.6 +/- 0.1 vs. 39.4 +/- 0.1 degrees C), short-term leukopenia followed by leukocytosis (6.44 +/- 0.4 vs. 5.69 +/- 0.3 x 10(6) cells/mL), an increased SCC (log(10) 2.1 +/- 0.1 vs. log(10) 2.8 +/- 0.1 x 10(3) cells/mL), heart rate (76 +/- 1 vs. 93 +/- 1 beats/min), and respiratory rate (32 +/- 2 vs. 36 +/- 1 breaths/min) in the acute phase of the disease. The LPS treatment upregulated the hepatic expression of TNF-alpha (103 +/- 24 vs. 255 +/- 18 units), IL-1beta (37 +/- 23 vs. 296 +/- 18 units), IL-6 (8 +/- 17 vs. 122 +/- 12 units), and IL-10 (130 +/- 66 vs. 541 +/- 50 units), and SAA3 (64 +/- 36 vs. 128 +/- 28 units) and Hp (9 +/- 82 vs. 762 +/- 65 units) reaching maximum levels at 3 to 6 h and 9 to 12 h postinfusion, respectively. Plasma concentrations of TNF-alpha (nondetectable vs. 1.9 +/- 0.3 ng/mL), SAA (19.8 +/- 19.4 vs. 149.7 +/- 15.5 microg/mL) and Hp (71.4 +/- 143.7 vs. 1,013.8 +/- 111.5 microg/mL) were elevated in the LPS-infused cows at 4 to 12 h, 8 to 120 h, and 24 to 120 h postinfusion, respectively. The hepatic expression of AGP and the AGP plasma concentration remained unaltered in LPS-induced cows. In conclusion, a minimally invasive liver biopsy technique can be used for studying the hepatic APR in diseased cattle. Lipopolysaccharide-induced mastitis resulted in a time-dependent production of inflammatory cytokines and SAA and Hp in the liver of dairy cows.

Identification of potential markers in blood for the development of subclinical and clinical mastitis in dairy cattle at parturition and during early lactation.

Our objective was to identify specific blood markers as risk factors for the development of mastitis during early lactation. We used a subset of cows from a larger experiment that consisted of a total of 634 lactations from 317 cows. Cows were of 3 breeds and ranged from parity 1 to 4. Blood samples were collected weekly from 56 d before expected calving date through 90 d in milk (DIM). Blood was analyzed for several hormones, metabolites, and enzymes, and energy intake and energy balance were calculated. Veterinary treatment records and daily composite milk somatic cell counts were analyzed and used to determine incidence and severity of mastitis in early lactation. Cows were separated into 2 groups: 1) WK0, consisting of cows that developed clinical mastitis (CM), cows that developed subclinical mastitis (SM), or cows that were healthy (H) during the first 7 DIM; and 2) EL, consisting of CM, SM, or H cows during wk 2 through 13 of lactation. Data were adjusted for numerous fixed effects (e.g., parity, breed, season, and DIM) before statistical analysis. The time of mastitis (TOM) was recorded as the DIM in which the first rise in somatic cell count was observed and was recorded as TOM = 0. The time before and after TOM was distinguished as +/- n wk relative to TOM = 0. Healthy cows were paired with either a SM or CM cow and the TOM for each H cow was equal to the TOM for its paired SM or CM cow. Data from wk -1 and -2 relative to TOM were analyzed for group WK0 and EL, respectively. For all parameters, SM cows did not differ from H cows from either group. The CM cows had higher nonesterified fatty acid levels and a tendency toward higher beta-hydroxybutyrate levels than H cows before mastitis for both groups. For group WK0, glucose was higher -1 wk relative to calving in CM than H cows. For group EL, aspartate aminotransferase was higher -2 wk relative to mastitis in CM than H cows during 8 to 90 DIM. All other variables were similar among CM, SM, and H cows for both groups. Our results indicate that substances in blood, especially nonesterified fatty acids and aspartate aminotransferase, may be potential markers for the risk of mastitis in early lactation.

Potential of milk mid-IR spectra to predict metabolic status of cows through blood components and an innovative clustering approach.

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and ß-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R 2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R 2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.

Glucose homeostasis and metabolic adaptation in the pregnant and lactating sheep are affected by the level of nutrition previously provided during her late fetal life.

This study investigated whether undernutrition (UN) during late fetal life can programme the subsequent adult life adaptation of glucose homeostasis and metabolism during pregnancy and lactation. Twenty-four primiparous experimental ewes were used. Twelve had been exposed to a prenatal NORM level of nutrition (maternal diet approximately 15 MJME/d) and 12 to a LOW level of nutrition (maternal diet approximately 7 MJME/d) during the last 6 weeks pre-partum. The experimental ewes were subjected to two intravenous glucose tolerance tests (IGTT) in late gestation (one prior to (G-IGTT) and one by the end of a feed restriction period (RG-IGTT)), and a third around peak lactation (L-IGTT). LOW had lower basal insulin concentrations during lactation, and significantly decreased absolute insulin secretion during the L-IGTT in spite of similar glucose tolerance, indicating increased insulin sensitivity in LOW during lactation. There was no effect of prenatal UN on glucose tolerance during G-IGTT, however, during RG-IGTT LOW was more glucose intolerant and apparently more insulin resistant compared to NORM. In conclusion, UN during late fetal life in sheep impairs subsequent pancreatic insulin secretory capacity during adult life, and reduces plasticity of down-regulation of insulin secretion in response to a metabolic challenge. Furthermore, prenatal UN appears to programme mechanisms, which in young adult females can shift the insulin hypersensitivity observed during early lactation into an insulin resistance observed during late gestation and feed restriction. Early postnatal UN caused by lowered milk intake in early postnatal life may have contributed to these phenomena.